class_docstr: Write me
      
code: def compute_q_values(self, state):
      q_values = self.compute_batch_q_values([state]).flatten()
      assert q_values.shape == (self.nb_actions,)
      return q_values
  
imports: import collections
  import numpy
  from keras.callbacks import History
  from keras.models import Model
  from keras.layers import Input, Lambda
  import keras.backend
  from rl.core import Agent
  from rl.agents.dqn import mean_q
  from rl.util import huber_loss
  from rl.policy import EpsGreedyQPolicy, GreedyQPolicy
  from rl.util import get_object_config
label_desc: Use image node_id 3 for calling the SARSAAgent obj's underlying member method code with example usage: obj.compute_q_values(state) and returns: q_values